Adaptive Edge Intelligence: Context-Aware and Federated Systems
IEEE CIS San Diego's 2025 Invited Seminar Series (Virtual)
In this talk, Dr. Yadav will be talking about his research on Edge Artificial Intelligence (Edge AI).
Edge Artificial Intelligence (Edge AI) is ushering in a new paradigm where computation moves closer to data sources, enabling real-time perception, privacy-preserving analytics, and autonomous decision-making in the physical world. Central to this evolution is context-aware computing, where systems sense, interpret, and respond to environmental, behavioral, and temporal cues. From gesture-driven interfaces to health monitoring, robotics, and smart infrastructure, tomorrow’s intelligent edge systems must dynamically adapt to changing context rather than operate as static inference engines. However, selecting optimal hardware platforms for these applications remains a non-trivial challenge, given diverse constraints in compute, memory, power, latency, and privacy. To address this, we introduce Edge-X, a cost-factor evaluation workflow that enables systematic selection and deployment of AI models on edge platforms (Conley,Yadav et al., 2025). Edge-X formalizes a step-by-step method to profile resource needs, map workload characteristics, and rapidly deploy applications across heterogeneous devices. Demonstrated through gesture recognition on three hardware tiers, Edge-X provides actionable insights into balancing capability, energy efficiency, and integration complexity.
This talk extends the Edge-X foundation to explore the future of context-aware edge intelligence - where devices evolve from inference units to modelers, adaptive learners, and federated participants capable of on-device personalization and collaborative learning across distributed ecosystems. We examine emerging processor architectures, context-aware model design, low-power continual-learning approaches, and federated protocols that respect privacy while enabling collective intelligence. The presentation will deliver a grounded deployment framework and a forward-looking roadmap toward self-training, situationally-aware, and cooperative Edge AI systems powering next-generation interactive, intelligent environments.
Date and Time
Location
Hosts
Registration
-
Add Event to Calendar
Loading virtual attendance info...
- Starts 05 November 2025 10:00 PM UTC
- Ends 13 November 2025 02:00 AM UTC
- No Admission Charge
Speakers
Nikhil Yadav of University of San Diego
Adaptive Edge Intelligence: Context-Aware and Federated Systems
Biography:
Dr. Nikhil Yadav is an Associate Professor and Chair of the Department of Computer Science at the University of San Diego (USD). His research explores edge intelligence, federated learning, quantum-enhanced machine learning, and context-aware systems, enabling devices to sense, interpret, and adapt in real time under resource constraints. His recent research proposes a systematic methodology for evaluating and deploying machine learning models across heterogeneous edge platforms, reducing development time and improving hardware-model alignment. Dr. Yadav also investigates Quantum Neural Network (QNN) benchmarking to evaluate the potential of quantum-accelerated learning pipelines and their future integration into distributed and edge-centric AI ecosystems.
Dr. Yadav previously served as Associate Professor of Computer Science and Program Director of IT programs at St. John’s University in New York City, leading interdisciplinary student-centered research, innovation, and experiential learning initiatives. He received his PhD in Computer Engineering from the University of Notre Dame, where he researched and implemented speech biomarker extraction and analysis using machine learning to identify mild Traumatic Brain Injuries (mTBIs). He has mentored numerous undergraduate and graduate research teams, secured industry and academic partnerships, and leads the engineering entrepreneurship program at USD, fostering collaboration across computing, engineering, and business. His experience spans academic scholarship, applied industry collaboration, entrepreneurship, and technology-driven education aligned with ABET and next-generation workforce needs.
Agenda
- Invited talk from Dr. Nikhil Yadav, Associate Professor and Chair of Computer Science at the University of San Diego, San Diego.
- Q/A Session